Vision Models for High Dynamic Range and Wide Colour Gamut Imaging
To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. This tutorial provides university researchers and graduate students in image processing, computer science & engineering and vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies.
It discusses their impact on image processing research and applications, as well as open challenges and future directions of research.
Marcelo Bertalmío (Montevideo, 1972) is a full professor at Universitat Pompeu Fabra, Spain, in the Information and Communication Technologies Department. He received the B.Sc. and M.Sc. degrees in electrical engineering from the Universidad de la República, Uruguay, and the Ph.D. degree in electrical and computer engineering from the University of Minnesota, USA, in 2001. He was awarded the 2012 SIAG/IS Prize of the Society for Industrial and Applied Mathematics (SIAM) for co-authoring the most relevant image processing work published in the period 2008-2012. He has received the Femlab Prize, the Siemens Best Paper Award, the Ramon y Cajal Fellowship, and the ICREA Academia Award, among other honours. He was Associate Editor for SIAM-SIIMS and elected secretary of SIAM’s activity group on imaging. Has obtained an ERC Starting Grant for his project “Image processing for enhanced cinematography” and two ERC Proof of Concept Grants to bring to market tone mapping and gamut mapping technologies. He’s co-coordinator of two H2020 projects involving world-leading companies in the film industry. Has written a book titled “Image Processing for Cinema”, published by CRC Press in 2014, edited the book “Denoising of Photographic Images and Video” published by Springer in 2018, and written a book titled “Vision models for high dynamic range and wide colour gamut imaging” published by Elsevier in November 2019. His current research interests are in developing image processing algorithms for cinema that mimic neural and perceptual processes in the visual system, and to investigate new vision models based on the efficient representation principle, with fine-tuning by movie professionals.